# Evolving Digital Circuits for the Knapsack Problem

arXiv: https://arxiv.org/abs/2109.13107 · HTML: https://mlsanity.com/paper/2109.13107/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 0 of its 7 references that are in the map.
- First posted on arXiv 21 Aug 2021.

## Built on by (most cited first, 1 of 1)

- [New Evolutionary Computation Models and their Applications to Machine Learning](https://mlsanity.com/paper/2110.00468/) (2021)

## Abstract (arXiv)

Multi Expression Programming (MEP) is a Genetic Programming variant that uses linear chromosomes for solution encoding. A unique feature of MEP is its ability of encoding multiple solutions of a problem in a single chromosome. In this paper we use Multi Expression Programming for evolving digital circuits for a well-known NP-Complete problem: the knapsack (subset sum) problem. Numerical experiments show that Multi Expression Programming performs well on the considered test problems.